Abstract
<title>Abstract</title> <p> <bold>Background:</bold> Sepsis, characterized by life-threatening organ dysfunction, arises from an imbalance in the host's response to infection, posing a significant threat to human health. Recent research indicates that the development of sepsis is associated with specific genetic factors. <bold>Objective:</bold> This study involved the collection of peripheral blood samples from both sepsis patients and healthy volunteers for high-throughput RNA sequencing. Following rigorous quality control of the sequenced genes, bioinformatics techniques were employed for further analysis. Differentially expressed genes identified through screening were subjected to Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment, and protein-protein interaction (PPI) core gene analysis. Additionally, quantitative PCR (qPCR) experiments, meta-analysis, and single-cell localization analysis were conducted on the potential sepsis risk genes identified. Ultimately, this process led to the identification of sepsis risk genes. <bold>Methods:</bold> In this study, peripheral blood samples were collected from 23 patients with sepsis and 10 healthy volunteers for gene sequencing. The sequencing process was facilitated by BGI Genomics. The resulting sequencing data, following quality control, were analyzed using the online platform iDEP 2.10 (http://bioinformatics.sdstate.edu/idep/) to identify differentially expressed genes. Subsequently, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted on the identified differentially expressed genes. To further explore the core genes from multiple perspectives, we employed the STRING database (https://cn.string-db.org/) to construct protein-protein interaction (PPI) networks, thereby elucidating the interactions between genes at the protein level. Following the identification of core genes, sepsis-related datasets (GSE28750, GSE54514, GSE67652, GSE69528, and GSE95233) were retrieved from the Gene Expression Omnibus (GEO) public database and categorized into sepsis and control groups for further analysis.The transcriptional levels of the genes S100A8, S100A9, and S100A12 were analyzed through meta-analysis. Subsequently, these selected genes will undergo single-cell localization analysis utilizing an online visualization platform to preliminarily assess their expression across various monocyte cell clusters. Finally, human mononuclear macrophages (THP-1 cells) were cultured and segregated into a control group and a sepsis model group. Quantitative real-time PCR (qPCR) was employed to quantify the gene expression levels of S100A8, S100A9, and S100A12. <bold>Results</bold> : A comprehensive analysis identified 1,108 differentially expressed genes (DEGs) when comparing the normal cohort to the sepsis cohort, with 737 genes exhibiting upregulation and 371 genes exhibiting downregulation. Notably, the genes S100A8, S100A9, and S100A12 occupy central positions within the protein-protein interaction (PPI) network. Functional enrichment analysis indicates their potential involvement in several signaling pathways, including the "PI3K-Akt signaling pathway," "Cell cycle," "Staphylococcus aureus infection," "Hematopoietic cell lineage," and "Transcriptional misregulation in cancer." Furthermore, meta-analysis corroborates the elevated expression of S100A8, S100A9, and S100A12 in patients with sepsis. Visual analysis reveals that these genes are predominantly expressed in macrophages. Quantitative PCR (qPCR) assays further confirm the heightened expression levels of S100A8, S100A9, and S100A12 in sepsis-affected cells. <bold>Conclusion</bold> : The expression levels of S100A8, S100A9, and S100A12 are significantly elevated in patients with sepsis. Functional enrichment analysis of differentially expressed genes, as identified by KEGG, indicates an association with the PI3K-Akt signaling pathway when compared to a normal cohort. Visualization analysis of single-cell localization reveals that S100A8, S100A9, and S100A12 are predominantly expressed in macrophages. These findings lead us to hypothesize that S100A8, S100A9, and S100A12 may play a role in immune regulation during sepsis. </p>